Publications

Our publications provide insight into some of our leading-edge research.

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  • 135 results found

2020

Post-Render Warp with Late Input Sampling Improves Aiming Under High Latency Conditions
Joohwan Kim, Pyarelal Knowles, Josef Spjut, Ben Boudaoud, Morgan McGuire
ꟻLIP: A Difference Evaluator for Alternating Images
Pontus Ebelin, Jim Nilsson, Tomas Akenine-Möller, Magnus Oskarsson, Kalle Åström, Mark D. Fairchild
Wolfgang Straßer Award for 3rd best paper, High Performance Graphics 2020
Learning Algebraic Multigrid Using Graph Neural Networks
Ilay Luz, Meirav Galun, Haggai Maron, Ronen Basri, Irad Yavneh
On Learning Sets of Symmetric Elements
Haggai Maron, Or Litany, Gal Chechik, Ethan Fetaya
Outstanding Paper, ICML 2020
NVAE: A Deep Hierarchical Variational Autoencoder
Arash Vahdat, Jan Kautz
Compositional Neural Scene Representations for Shading Inference
Jonathan Granskog, Fabrice Rousselle, Marios Papas, Jan Novák
Understanding SSIM
Jim Nilsson, Tomas Akenine-Möller
ML-driven Malware that Targets AV Safety
Saurabh Jha, Shengkun Cui, Subho S. Banerjee, James Cyriac, Timothy Tsai, Zbigniew T. Kalbarczyk, Ravishankar K. Iyer
A Taxonomy of Bidirectional Scattering Distribution Function Lobes for Rendering Engineers
Morgan McGuire, Julie Dorsey, John F. Hughes, Steve Marschner, Matt Pharr, Peter Shirley
Neural Denoising with Layer Embeddings
Jacob Munkberg, Jon Hasselgren
PyTorchFI: A Runtime Perturbation Tool for DNNs
Abdulrahman Mahmoud, Neeraj Aggarwal, Alex Nobbe, Jose Rodrigo Sanchez Vicarte, Sarita V. Adve, Christopher W. Fletcher, Iuri Frosio, Siva Hari
DREAMPlace: Deep Learning Toolkit-Enabled GPU Acceleration for Modern VLSI Placement
Yibo Lin, Zixuan Jiang, Jiaqi Gu, Wuxi Li, Shounak Dhar, Haoxing (Mark) Ren, Brucek Khailany, David Z. Pan
2021 IEEE Transactions on Computer-Aided Design Donald O. Pederson Best Paper Award
Contrastive Learning for Weakly Supervised Phrase Grounding
Tanmay Gupta, Arash Vahdat, Gal Chechik, Xiaodong Yang, Jan Kautz, Derek Hoiem
Bi3D: Stereo Depth Estimation via Binary Classifications
Abhishek Badki, Alejandro Troccoli, Kihwan Kim, Jan Kautz, Pradeep Sen, Orazio Gallo
Meshlet Priors for 3D Mesh Reconstruction
Abhishek Badki, Orazio Gallo, Jan Kautz, Pradeep Sen
Instance-aware, Context-focused, and Memory-efficient Weakly Supervised Object Detection
Zhongzheng Ren, Zhiding Yu, Xiaodong Yang, Ming-Yu Liu, Yong Jae Lee, Alexander G. Schwing, Jan Kautz
Regularizing Neural Networks via Minimizing Hyperspherical Energy
Weiyang Liu, Rongmei Lin, Zhen Liu, Chen Feng, Zhiding Yu, James M. Rehg, Li Xiong, Le Song
Monte Carlo Gradient Quantization
Goncalo Mordido, Matthijs Van keirsbilck, Alex Keller
Analyzing and Improving the Image Quality of StyleGAN
Tero Karras, Samuli Laine, Miika Aittala, Janne Hellsten, Jaakko Lehtinen, Timo Aila
Novel View Synthesis of Dynamic Scenes with Globally Coherent Depths
Jae shin Yoon, Kihwan Kim, Orazio Gallo, Hyunsoo Park, Jan Kautz
Two-shot Spatially-varying BRDF and Shape Estimation
Mark Boss, Varun Jampani, Kihwan Kim, Hendrik P.A. Lensch, Jan Kautz
Dreaming to Distill: Data-free Knowledge Transfer via DeepInversion
Hongxu Danny Yin, Pavlo Molchanov, Jose M. Alvarez, Zhizhong Li, Arun Mallya, Derek Hoiem, Niraj K. Jha, Jan Kautz
Self-Supervised Viewpoint Learning From Image Collections
Siva Karthik Mustikovela, Varun Jampani, Shalini De Mello, Sifei Liu, Umar Iqbal, Carsten Rother, Jan Kautz
EMOGI: Efficient Memory-access for Out-of-memory Graph-traversal In GPUs
Seung Won Min, Vikram Sharma Mailthody, Zaid Qureshi, Jinjun Xiong, Eiman Ebrahimi, Wen-mei Hwu
MVLidarNet: Real-Time Multi-Class Scene Understanding for Autonomous Driving Using Multiple Views
Ke Chen, Ryan, Nikolai, Stan Birchfield, Alexander Popov, David Wehr, Ibrahim Eden, Joachim Pehserl
Making Convolutions Resilient via Algorithm-Based Error Detection Techniques
Siva Hari, Michael B. Sullivan, Timothy Tsai, Steve Keckler
Learning Canonical Representations for Scene Graph to Image Generation
Roei Herzig, Amir Bar, Huijuan Xu, Gal Chechik, Trevor Darrell, Amir Globerson
There’s Plenty of Room at the Top: What Will Drive Computer Performance after Moore’s Law?
Charles E. Leiserson, Neil C. Thompson, Joel Emer, Bradley C. Kuszmaul, Butler W. Lampson, Daniel Sanchez , Tao B. Schardl
Buddy Compression: Enabling Larger Memory for Deep Learning and HPC Workloads on GPUs
Esha Chouske, Michael B. Sullivan, Mike O'Connor, Mattan Erez, Jeff Pool, David Nellans, Steve Keckler
Weakly-Supervised 3D Human Pose Learning via Multi-view Images in the Wild
Umar Iqbal, Pavlo Molchanov, Jan Kautz
6-DOF Grasping for Target-driven Object Manipulation in Clutter
Adithyavairavan Murali, Arsalan Mousavian, Clemens Eppner, Chris Paxton, Dieter Fox
Best Paper Finalist in Robot Manipulation, ICRA 2020
Best Student Paper Finalist, ICRA 2020
Motion reasoning for goal-based imitation learning
De-An Huang, Yu-Wei Chao, Chris Paxton, Xinke Deng, Li Fei-Fei, Juan Carlos Niebles, Animesh Garg, Dieter Fox